Agent based modeling of relapsing multiple sclerosis: A possible approach to predict treatment outcome

Francesco Pappalardo, Giulia Russo, Marzio Pennisi, Giuseppe Sgroi, Giuseppe Alessandro, Parasiliti Palumbo, Santo Motta, Davide Maimone, Ferdinando Chiacchio

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

In this work, we present the application of a computational modeling infrastructure named UISS (Universal Immune System Simulator) able to simulate the main features and dynamics of the immune system activities. We provide an extended version of UISS to simulate all the underlying MS pathogenesis and its interaction with the host immune system. We simulated MS patients with different relapsing-remitting courses. Even though the model can be further personalized employing immunological parameters and genetic information, based on the available data, we obtained simulation scenarios for each patient who matched the real clinical and MRI history. UISS may have the potential to assist MS specialists in predicting the course of the disease and the response to treatment.

Original languageEnglish
Title of host publicationProceedings - 2018 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2018
EditorsHarald Schmidt, David Griol, Haiying Wang, Jan Baumbach, Huiru Zheng, Zoraida Callejas, Xiaohua Hu, Julie Dickerson, Le Zhang
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1380-1385
Number of pages6
ISBN (Electronic)9781538654880
DOIs
Publication statusPublished - 21 Jan 2019
Externally publishedYes
Event2018 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2018 - Madrid, Spain
Duration: 3 Dec 20186 Dec 2018

Publication series

NameProceedings - 2018 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2018

Conference

Conference2018 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2018
Country/TerritorySpain
CityMadrid
Period3/12/186/12/18

Keywords

  • artificial immune system
  • immune modeling
  • multiple sclerosis
  • personalized therapy

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